So currently I have been using cn.mops for CNV detection. The result for one sample is confusing since there is overlap between different CNV regions in cnvr output.

It reads as follows:

It appeared to be an overlapping in chr7 with [86116372,115099423] assigned with CN2 while in the previous line it was given CN4. It's confusing, so I re-check the cnvs output.

It reads:

It's not overlapping however it doesn't exactly consistent with cnvr output.

SO the question is: which output should I use? Is there an explanation for the difference between cnvr and cnvs? what may be the cause of the cnvr results overlapping?

Here is the command I use:

library(cn.mops)

BAMFiles <- c('/home/export/data/P101SC17020317-01juyongzhi/Results/Bam/1315_1.final.bam','/home/export/data/P101SC17020317-01juyongzhi/Results/Bam/1315_2.final.bam','/home/export/data/P101SC17020317-01juyongzhi/Results/Bam/sq1315_pbmc.final.bam')

segments <- read.table('/home/export/data/1194/bam/result_bed_no_chr.txt',sep="\t",as.is=TRUE)

segments <- unique(segments)

gr <- GRanges(segments[,1],IRanges(segments[,2],segments[,3]))

X <- getSegmentReadCountsFromBAM(BAMFiles,GR=gr)    

resRef <- referencecn.mops(cases=X[,1],controls=X[,3],classes=c("CN0", "CN1", "CN2", "CN3", "CN4", "CN5", "CN6","CN7","CN8","CN16","CN32","CN64","CN128"),I = c(0.025, 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 8, 16, 32, 64),segAlgorithm="DNAcopy")

resRef <- calcIntegerCopyNumbers(resRef)

segm <- as.data.frame(segmentation(resRef))
CNVs <- as.data.frame(cnvs(resRef))
CNVRegions <- as.data.frame(cnvr(resRef))
    write.csv(segm,file="/home/export/CG/copynumber_clonal_evolution/result/1315/1315_1_segmentation.csv") 
    write.csv(CNVs,file="/home/export/CG/copynumber_clonal_evolution/result/1315/1315_1_cnvs.csv")
    write.csv(CNVRegions,file="/home/export/CG/copynumber_clonal_evolution/result/1315/1315_1_cnvr.csv")

Sorry for the late response - I thought we clarified this via email.

The segments in the CNVR slot are a union of the individual CNVs. For example, if individual A has a CNV in segments 3 and 4, and individual B has a CNV in segment 4 and 5, the CNVR-slot will contain a CNV-region spanning the three segments [3,4,5].

So, if you are looking for CNVs in individuals with accurate breakpoints, you should use the "CNVS"-slot. If you are looking for regions with high genetic variance (e.g. for GWAS-studies to decrease FDR and increase discovery power), you can use the CNV regions (CNVR).

Regards,

Günter